Técnicas de análisis de posproceso en resonancia magnetica para el estudio de la conectividad cerebral

Iglesia-Vayá, María de la; Molina‐Mateo, José; Escarti-Fabra, M.J.; Martí‐Bonmatí, Luis; Robles, Montserrat; Meneu, Teresa; Aguilar, Eduardo J.; Sanjuán, Julio

doi:10.1016/j.rx.2010.11.007

Cited by 6 publications

(10 citation statements)

References 45 publications

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“…Furthermore, the degree of functional connectivity is related to all the direct and indirect structural connections between the elements of a system. Thus, while strong functional connectivity between two areas may be suggestive of strong structural connectivity, it does not necessarily mean that the two areas are directly connected [100]. …”

Section: Discussionmentioning

confidence: 99%

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

et al. 2017

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In the setting of profound ocular blindness, numerous lines of evidence demonstrate the existence of dramatic anatomical and functional changes within the brain. However, previous studies based on a variety of distinct measures have often provided inconsistent findings. To help reconcile this issue, we used a multimodal magnetic resonance (MR)-based imaging approach to provide complementary structural and functional information regarding this neuroplastic reorganization. This included gray matter structural morphometry, high angular resolution diffusion imaging (HARDI) of white matter connectivity and integrity, and resting state functional connectivity MRI (rsfcMRI) analysis. When comparing the brains of early blind individuals to sighted controls, we found evidence of co-occurring decreases in cortical volume and cortical thickness within visual processing areas of the occipital and temporal cortices respectively. Increases in cortical volume in the early blind were evident within regions of parietal cortex. Investigating white matter connections using HARDI revealed patterns of increased and decreased connectivity when comparing both groups. In the blind, increased white matter connectivity (indexed by increased fiber number) was predominantly left-lateralized, including between frontal and temporal areas implicated with language processing. Decreases in structural connectivity were evident involving frontal and somatosensory regions as well as between occipital and cingulate cortices. Differences in white matter integrity (as indexed by quantitative anisotropy, or QA) were also in general agreement with observed pattern changes in the number of white matter fibers. Analysis of resting state sequences showed evidence of both increased and decreased functional connectivity in the blind compared to sighted controls. Specifically, increased connectivity was evident between temporal and inferior frontal areas. Decreases in functional connectivity were observed between occipital and frontal and somatosensory-motor areas and between temporal (mainly fusiform and parahippocampus) and parietal, frontal, and other temporal areas. Correlations in white matter connectivity and functional connectivity observed between early blind and sighted controls showed an overall high degree of association. However, comparing the relative changes in white matter and functional connectivity between early blind and sighted controls did not show a significant correlation. In summary, these findings provide complimentary evidence, as well as highlight potential contradictions, regarding the nature of regional and large scale neuroplastic reorganization resulting from early onset blindness.

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Section: Discussionmentioning

confidence: 99%

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

et al. 2017

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“…One of the most frequently used and largest diffusion MRI datasets are the public releases of the Human Connectome Project (HCP) [5]. Numerous publications are applying HCP data in different contexts, e.g., [6–12].…”

Section: Introductionmentioning

confidence: 99%

High-resolution directed human connectomes and the Consensus Connectome Dynamics

et al. 2019

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Here we show a method of directing the edges of the connectomes, prepared from HARDI datasets from the human brain. Before the present work, no high-definition directed braingraphs were published, because the tractography methods in use are not capable of assigning directions to the neural tracts discovered. Previous work on the functional connectomes applied low-resolution functional MRI-detected statistical causality for the assignment of directions of connectomes of typically several dozens of vertices. Our method is based on the phenomenon of the “Consensus Connectome Dynamics”, described earlier by our research group. In this contribution, we apply the method to the 423 braingraphs, each with 1015 vertices, computed from the public release of the Human Connectome Project, and we also made the directed connectomes publicly available at the site http://braingraph.org . We also show the robustness of our edge directing method in four independently chosen connectome datasets: we have found that 86% of the edges, which were present in all four datasets, get the same directions in all datasets; therefore the direction method is robust. While our new edge-directing method still needs more empirical validation, we think that our present contribution opens up new possibilities in the analysis of the high-definition human connectome.

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“…Sin embargo, en la actualidad se conoce que las estructuras que se involucran con la activación de un proceso cognitivo no trabajan de manera independiente, por el contrario, se involucra la activación de varias regiones cerebrales que interactúan entre sí para dar lugar a circuitos neuronales y estados de conducta. A lo anterior se le conoce como integración funcional [58], [59]. La interacción entre ambos principios de organización funcional en las redes neuronales genera patrones (vinculados anatómicamente, estadísticamente o causalmente) que describen la conexión y el flujo de la información entre un sistema y otro (ver fig.…”

Section: Antecedentes 21 ¿Qué Es La Conectividad?unclassified

“…La conectividad estructural se define como la conexión física entre uno o varios conjuntos de neuronas. Este tipo de conectividad establece como se encuentran vinculadas de manera física las regiones cerebrales, formando circuitos que permiten dar lugar a funciones cognitivas complejas [59], [62]. Los análisis de la conectividad estructural se emplean mayormente en dos casos: patologías cerebrales [63], así como, en el trazado de las fibras de los axones (materia blanca) [64], [65].…”

Section: Conectividad Estructuralunclassified

“…Esta interacción funcional es calculada entre todos los elementos de un sistema sin importar si estos están conectados estructuralmente o no. La interrelación que estas estructuras presentan se determina por la fluctuación de patrones estadísticos que fluctúan en distintas escalas de tiempo (dependencia estadística entre ellas) y puede calcularse por medidas de correlación o covarianza [58], [59].…”

Section: Conectividad Funcionalunclassified

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Análisis de la conectividad efectiva y funcional en los paradigmas de memoria de trabajo, anticipación a la recompensa y reconocimiento facial de emociones :un estudio de resonancia magnética funcional (FMRI)

Ruiz

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Técnicas de análisis de posproceso en resonancia magnetica para el estudio de la conectividad cerebral

Cited by 6 publications

References 45 publications

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

High-resolution directed human connectomes and the Consensus Connectome Dynamics

Análisis de la conectividad efectiva y funcional en los paradigmas de memoria de trabajo, anticipación a la recompensa y reconocimiento facial de emociones :un estudio de resonancia magnética funcional (FMRI)

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